Design And Realization Of Smart Station's State Assessment And Early Warning System

As we all know,China's high-speed rail technology development and management construction are advancing at a rapid pace.As the best choice for passengers to travel today,managers have put forward higher requirements for the convenience and comfort of high-speed rail stations' operating environment,so that to meet the passengers' higher requirements for travel experience and travel safety.Therefore,it is of inestimable market value and significance to create an intelligent high-speed rail station with safe,comfortable and convenient operating environment.However,there is a certain lag of the traditional high-speed rail station monitoring management system,and the staffs cannot promptly find out the cause of the problem,the scope of its impact,and the time required to resolve it.In order to solve the problems above,this paper proposes to design a station state assessment and early warning system based on the React framework and XGBoost model.Based on the intelligent station project,this system analysis the project requirements and architecture by Node.js and Egg.js frameworks used for system background development,which solves the problem of the vacant connection process of the traditional server,while improving the efficiency of the CPU.The Mongo DB database is used to store real-time data collected by various sensors and other manually input data,which solves the bloated problem when traditional My SQL and other relational databases store complex structures data.The XGBoost model is used for data analysis and processing then outputs assessment results,and it is able to make better use of parallel and distributed computing.Lastly,React framework,Ant Design library,Echarts library and other technologies are used to realize the front-end page display of the system,which improves the page loading performance with displaying data more intuitively and simplifing system maintenance and subsequent development steps.Such functions of environmental state monitoring management,equipment information management,assessment and early warning and user management,etc.can be realized eventually.Compared with other systems,the station state assessment and early warning system has the following characteristics:1.The system performs real-time monitoring of various environmental state parameters,human flow information,equipment information,etc.of the high-speed rail station.Based on this,the XGBoost model is used to analyze and process various environmental state data,and it provides a early warning prompt function,which helps managers judge the abnormal state of the environment during operating the high-speed rail station,so that they can detect abnormal problems in time and prevent accidents.2.The system implements data visualization through the collected data,combined with the open source React framework,Ant Design library,and Echarts library,so that time-varying data can be rendered to the front-end page of the system more quickly.By the test of whole the station state assessment and early warning system,the result shows that the system achieves an expected effect and it also fully meets the design requirements.The system can provide good help for the actual operation process of the high-speed rail station,and it also brings a more comfortable,convenient and safe travel experience for passengers.